Results 121 to 130 of about 1,742,725 (265)

Fundamental Challenges, Physical Implementations, and Integration Strategies for Ising Machines in Large‐Scale Optimization Tasks

Advanced Electronic Materials
Ising machines are specialized hardware solvers designed to solve computationally hard combinatorial optimization problems by finding ground states of the Ising model.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
doaj   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

Machine learning prediction of the mechanical properties of injection-molded polypropylene through X-ray diffraction analysis

Science and Technology of Advanced Materials
Predicting the mechanical properties of polymer materials using machine learning is essential for the design of next-generation of polymers. However, the strong relationship between the higher-order structure of polymers and their mechanical properties ...
Ryo Tamura, Kenji Nagata, Keitaro Sodeyama, Kensaku Nakamura, Toshiki Tokuhira, Satoshi Shibata, Kazuki Hammura, Hiroki Sugisawa, Masaya Kawamura, Teruki Tsurimoto, Masanobu Naito, Masahiko Demura, Takashi Nakanishi   +12 more
doaj   +1 more source

Josephson parametric oscillator based Ising machine

Physical Review B
9 pages, 10 figures, 31 references.
Sasan Razmkhah, Mehdi Kamal, Nobuyuki Yoshikawa, Massoud Pedram   +3 more
openaire   +3 more sources

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Materials Representation Learning Based on a Material–Motif Network and Heterogeneous Graphs

Advanced Intelligent Discovery, EarlyView.
Structure motifs in materials are used to construct a bipartite material–motif network that links each material to its constituent motifs and establishes connectivity among materials sharing common motifs. Network analysis reveals material clusters associated with different functional applications and supports motif‐guided screening of materials.
Anoj Aryal, Weiyi Gong, Huta Banjade, Qimin Yan   +3 more
wiley   +1 more source

The NADPH oxidase NOX4 regulates redox and metabolic homeostasis preventing HCC progression

Hepatology, EarlyView., 2022
Loss of NOX4 in HCC tumor cells induces metabolic reprogramming in a Nrf2/MYC‐dependent manner to promote HCC progression. Abstract Background and Aims The NADPH oxidase NOX4 plays a tumor‐suppressor function in HCC. Silencing NOX4 confers higher proliferative and migratory capacity to HCC cells and increases their in vivo tumorigenic potential in ...
Irene Peñuelas‐Haro, Rut Espinosa‐Sotelo, Eva Crosas‐Molist, Macarena Herranz‐Itúrbide, Daniel Caballero‐Díaz, Ania Alay, Xavier Solé, Emilio Ramos, Teresa Serrano, María L. Martínez‐Chantar, Ulla G. Knaus, José M. Cuezva, Antonio Zorzano, Esther Bertran, Isabel Fabregat   +14 more
wiley   +1 more source

A Comprehensive Comparative Study of Active Learning Schemes for Nanophotonics Design

Advanced Intelligent Discovery, EarlyView.
Active learning (AL) strategies are benchmarked for the binary design of planar multilayer nanophotonic structures. Factorization machines combined with quantum annealing (QA) become effective as dimensionality increases. Hybrid QA provides the strongest results for 100‐layer problems, highlighting the importance of optimization method selection in ...
Serang Jung, Seongmin Kim, Jaehyun Park, Chaeyoung Park, Zhihao Xu, Sanghyo Hwang, Baiqing Ye, Youn sang Kim, Sun‐Kyung Kim, Tengfei Luo, Eungkyu Lee   +10 more
wiley   +1 more source

A 50-spin surface acoustic wave Ising machine

Communications Physics
Time-multiplexed spinwave Ising Machines have unveiled a route towards miniaturized and low-cost combinatorial optimization solvers but are constrained in the number of spins by nonlinear spinwave dispersion.
Artem Litvinenko, Roman Khymyn, Roman Ovcharov, Johan Åkerman   +3 more
doaj   +1 more source

Photonic Ising Machine Using Parallel Bandit Architecture Based on Laser Chaos

IEEE Access
Photonic computing has emerged as a transformative technology for overcoming the fundamental limitations of semiconductor technology. Among recent advancements, the laser chaos decision maker has been introduced for ultrafast decision making by ...
Ryota Yasudo, Michihiro Koibuchi, Mikio Hasegawa   +2 more
doaj   +1 more source